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Harsh Kumar gaurav

@harshkumargaurav

Machine Learning Engineer building agentic AI systems, including a clinical RAG tool with 100% medication reconciliation accuracy.

India

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What I'm looking for

I’m looking to keep learning how to design engineered end-to-end ML pipelines and apply advanced AI techniques to real-world business challenges.

At MTMC Global, I built an end-to-end heart disease prediction backend pipeline using clinical records queried from SQL-based datasets. My preprocessing workflows improved data quality and model performance stability by 18%, and my Random Forest and XGBoost models achieved 88% and 90% test accuracy.

I developed MediAgent-RAG, an agentic clinical AI system that turns clinical PDFs into structured discharge summaries. Its core agent loop achieved 100% medication reconciliation accuracy with no-fabrication guarantees, and step-level observability and tests reduced critical decision-making failures by 40%.

I also created a LangGraph research agent that organizes research topics into workflows and produces PDF and Markdown reports through a Streamlit application. I’m focused on learning how to design engineered end-to-end ML pipelines and apply AI techniques to real-world business challenges.

Experience

Work history, roles, and key accomplishments

Machine Learning Intern

MTMC Global

Jan 2026 - Present (8 months)

Built an end-to-end Heart Disease Prediction backend pipeline covering data pre-processing, feature engineering, model training, and evaluation on 100,000+ structured clinical records. Implemented ensemble models using Random Forest and XGBoost, achieving 88% and 90% test accuracy respectively.